The Hindu Editorial Analysis- 18th April 2025 | Current Affairs & Hindu Analysis: Daily, Weekly & Monthly - UPSC PDF Download

A closer look at strategic affairs and the AI factor

 Why in News? 

Research on how AI affects global strategy is still very limited, and we currently have no way to know what superintelligent AI might be able to do.

Introduction

There is growing concern about a potential race to develop powerful AI weapons. There is much speculation about when we might achieve artificial general intelligence (AGI),. form of AI that could surpass human intelligence and autonomously tackle new challenges beyond its training. While many discussions focus on the increasing capabilities of AI, there is a lack of research on its implications for global strategy. A recent paper by Eric Schmidt and others contributes to this discussion, although some aspects of their analysis are questionable.

The AGI Debate & Strategic Preparation

• The proximity of AGI remains uncertain and is a topic of intense debate.
• Schmidt, Hendrycks, and Wang argue for the necessity of preparing for the risks associated with AGI, should it become a reality.
• This preparation involves addressing security threats and global competition related to advanced AI.

Importance of AI Non-Proliferation

• A commentary from RAND emphasizes the critical need for AI non-proliferation, which involves preventing powerful AI from falling into the hands of malicious actors.
• The commentary underscores the global risks posed by the potential misuse of dangerous AI tools.
• This concept is reminiscent of past efforts in nuclear arms control.

Questionable Comparisons: AI vs. Nuclear Weapons

• The authors draw parallels between AI risks and nuclear weapons, particularly through the concept of MAIM (Mutual Assured AI Malfunction).
• However, this comparison is flawed due to the significant differences in the construction, usage, and dissemination of AI compared to nuclear arms.
• Unlike nuclear weapons, AI is decentralized and collaborative, making it distinct from being confined to national laboratories.

Flawed Analogy: MAIM vs. MAD

Destroying Rogue AI Projects

• Proposal to sabotage terrorist or rogue AI initiatives
• High risk of error, escalation, and unintended consequences

AI’s Decentralized Nature

• AI is built by global teams across borders
• Hard to pinpoint and attack without harming innocent or unintended targets

Sabotage as Strategic Deterrence

• Authors support preemptive action against enemy AI
• Could justify aggressive military actions, increase global instability

Key Risks of the MAIM Approach

• Oversimplifying AI as a weapon may lead to poor strategic decisions.
• Encouraging sabotage or preemptive strikes based on imperfect intelligence could worsen conflicts.
• Policies based on flawed analogies like MAIM risk promoting militarized responses to complex, tech-driven threats.

Controlling AI Chips Like Nuclear Material: A Flawed Proposal

• The authors suggest controlling the distribution of AI chips in the same way enriched uranium is regulated for nuclear weapons.
• But this analogy doesn't work well because:
  • AI models, once trained, don’t need constant access to chips or materials like uranium.
  • Supply chains for AI are harder to track and control — making enforcement difficult.

Key Differences Between Nuclear Materials and AI Chips

Questionable Assumptions in the Paper

• The authors assume AI-based bioweapons and cyberattacks are inevitable without early state intervention.
• This is a worst-case scenario without clear supporting evidence.
• While AI could lower barriers to cyber threats, it’s not yet proven to justify being treated like a weapon of mass destruction.
• Another assumption: AI development will be led by states.
• In reality, the private sector currently leads AI innovation.
• Governments often adopt AI after it is developed by private firms, especially in defense or security.

Limits of Using Historical Analogies for AI Strategy

• Comparing AI to nuclear weapons can be misleading for policy planning.
• Though drawing from history is useful, AI operates differently:
  • It is developed, distributed, and deployed in ways that don’t resemble nuclear tech.
  • Assuming deterrence strategies used in the nuclear era will work for AI may lead to wrong policy choices.

Takeaway for Policymakers

• AI is dynamic, decentralized, and evolving rapidly — unlike nuclear weapons.
• Policymakers need to build new frameworks for AI governance rather than rely on outdated models.
• Historical analogies may help guide thinking but shouldn’t shape full strategies for handling future AI threats.

Need for more scholarship

• We need better examples and models to understand how AI fits into global strategy.
• One possible model is the General Purpose Technology (GPT) framework, which explains how powerful technologies spread across different areas and become key to a country’s strength.
• AI could be seen through this lens, but it doesn’t fully fit the GPT model right now.
• This is because current AI tools like large language models (LLMs) still have big limitations.
• These models are not yet advanced enough to spread and impact all sectors the way true GPTs do.

Conclusion

The only way countries can prepare to deal with superintelligent AI in the future is by doing more research on how AI affects global strategy.

However, the key questions are if such AI will ever exist and when it might appear — because right now, we have no way of knowing what it could actually do, and that uncertainty will shape how policies are made.